I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
Learning to Recognize Musical Genre from Audio : Challen..:
, In:
Companion Proceedings of the The Web Conference 2018
,
Defferrard, Michaël
;
Mohanty, Sharada P.
;
Carroll, Sean F.
. - p. 1921-1922 , 2018
Link:
https://dl.acm.org/doi/10.1145/3184558.3192310
RT T1
Companion Proceedings of the The Web Conference 2018
: T1
Learning to Recognize Musical Genre from Audio : Challenge Overview
UL https://suche.suub.uni-bremen.de/peid=acm-3192310&Exemplar=1&LAN=DE A1 Defferrard, Michaël A1 Mohanty, Sharada P. A1 Carroll, Sean F. A1 Salathé, Marcel PB International World Wide Web Conferences Steering Committee YR 2018 K1 ml challenge K1 music information retrieval (mir) K1 open data K1 Information systems K1 Information retrieval K1 Specialized information retrieval K1 Multimedia and multimodal retrieval K1 Music retrieval K1 Computing methodologies K1 Machine learning K1 Learning paradigms K1 Supervised learning SP 1921 OP 1922 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3184558.3192310 DO https://dl.acm.org/doi/10.1145/3184558.3192310 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)